Intelligent Systems II · TEE · papers

Q3(b) PSO maximization, supplied parameters [10]

Re-examination · 25 Jun 2024

Actual historical paper ·100 marks attempted /140 offered · Q1 compulsory + any four of Q2–Q7. Source defects and solution assumptions are explicitly identified.

Question. Q3(b) [10 marks · 2024-06-25]

Find the maximum of f (x)=−x²+5x+20 on −6≤x≤4 using PSO. Use four initial positions −5.6,−5.2,−1.1,2.3. Show detailed computations for iteration 1, with c₁=c₂=1, r₁=r₂=.5, w=1 and all initial velocities zero.

Answer

Given

The four x values; zero velocities; w=1, c₁=c₂=1, r₁=r₂=.5; bounded domain[−6,4].

To find

One iteration and the best value actually reached.

Formula and why it applies

v_i^{new}=wv_i+c_1r_1(pbest_i-x_i)+c_2r_2(gbest-x_i),\quad x_i^{new}=x_i+v_i^{new}LaTeX: v_i^{new}=wv_i+c_1r_1(pbest_i-x_i)+c_2r_2(gbest-x_i),\quad x_i^{new}=x_i+v_i^{new}

This is maximization: larger f is better. Initialize each pbest to its own initial position, and freeze the old gbest for the whole simultaneous update.

Solution

Step 1. Find initial fitness and gbest
ParticlePosition−x²5xf (x)
1-5.6-31.36-28.0-39.36
2-5.2-27.04-26.0-33.04
3-1.1-1.21-5.513.29
42.3-5.2911.526.21

Initial values [−39.36,−33.04,13.29,26.21]. Maximum 26.21 occurs at x=2.3.

Step 2. Compute new velocities

The first two terms are zero: old velocity=0 and pbest−x=0. Thus vnew=.5(2.3−x).

ParticleSocial differenceVelocityNew position
12.3−(-5.6)=7.9.5×(7.9)=3.95-5.6 + (3.95)=-1.65
22.3−(-5.2)=7.5.5×(7.5)=3.75-5.2 + (3.75)=-1.45
32.3−(-1.1)=3.4.5×(3.4)=1.7-1.1 + (1.7)=0.6
42.3−(2.3)=0.5×(0)=02.3 + (0)=2.3
Step 3. Evaluate the new positions
New x−x²+5x+20New fitness
-1.65−(-1.65)²+5(-1.65)+209.0275
-1.4500000000000002−(-1.45)²+5(-1.45)+2010.6475
0.5999999999999999−(0.6)²+5(0.6)+2022.64
2.3−(2.3)²+5(2.3)+2026.21

All new positions are in [−6,4], so no boundary repair is required.

Step 4. Update pbest and gbest

New positions [−1.65,−1.45,.6,2.3] give fitness [9.0275,10.6475,22.64,26.21]. The first three replace their worse personal records; the fourth ties its record. Global best remains 2.3 with 26.21.

As a separate analytical check, f (x)=26.25−(x−2.5)² has true maximum 26.25 at 2.5. PSO has not reached that point after this one iteration.

Final answer. After iteration 1: positions[−1.65,−1.45,.6,2.3], gbest=2.3, achieved fitness 26.21.